workqueue: Track and monitor per-workqueue CPU time usage

Now that wq_worker_tick() is there, we can easily track the rough CPU time
consumption of each workqueue by charging the whole tick whenever a tick
hits an active workqueue. While not super accurate, it provides reasonable
visibility into the workqueues that consume a lot of CPU cycles.
wq_monitor.py is updated to report the per-workqueue CPU times.

v2: wq_monitor.py was using "cputime" as the key when outputting in json
    format. Use "cpu_time" instead for consistency with other fields.

Signed-off-by: Tejun Heo <tj@kernel.org>

kernel/workqueue.c

@@ -212,6 +212,7 @@ struct worker_pool {
 enum pool_workqueue_stats {
 	PWQ_STAT_STARTED,	/* work items started execution */
 	PWQ_STAT_COMPLETED,	/* work items completed execution */
+	PWQ_STAT_CPU_TIME,	/* total CPU time consumed */
 	PWQ_STAT_CPU_INTENSIVE,	/* wq_cpu_intensive_thresh_us violations */
 	PWQ_STAT_CM_WAKEUP,	/* concurrency-management worker wakeups */
 	PWQ_STAT_MAYDAY,	/* maydays to rescuer */
@@ -1136,6 +1137,8 @@ void wq_worker_tick(struct task_struct *task)
 	if (!pwq)
 		return;
 
+	pwq->stats[PWQ_STAT_CPU_TIME] += TICK_USEC;
+
 	/*
 	 * If the current worker is concurrency managed and hogged the CPU for
 	 * longer than wq_cpu_intensive_thresh_us, it's automatically marked